Research · Thursday 15 October 2026 · story 9
Agent-Reflex paper trains agents to reflect under noisy tool feedback
Hugging Face reports a paper that proposes Agent-Reflex, a three-stage framework to train language agents for proactive reflection under noisy tool feedback and user corrections. The paper says its Qwen3-8B version scored 58.6 overall across five long-horizon benchmarks for tool use, plus 29.1 on AgentNoiseBench.
Why it matters. It offers a training approach for agents that must recover from noisy MCP tool feedback and user corrections in real deployments.
Read the original at huggingface.co